ABSTRACT
Methylation sequencing is a promising approach to infer the tissue of origin of cell-free DNA (cfDNA). In this study, a single- and a double-stranded library preparation approach were evaluated with respect to their technical biases when applied on cfDNA from plasma and urine. Additionally, tissue of origin (TOO) proportions were evaluated using two deconvolution methods. Sequencing cfDNA from urine using the double-stranded method resulted in a substantial within-read methylation bias and a lower global methylation (56.0% vs. 75.8%, p ≤ 0.0001) compared to plasma cfDNA, both of which were not observed with the single-stranded approach. Individual CpG site-based TOO deconvolution resulted in a significantly increased proportion of undetermined TOO with the double-stranded method (urine: 32.3% vs. 1.9%; plasma: 5.9% vs. 0.04%; p ≤ 0.0001), but no major differences in proportions of individual cell types. In contrast, fragment-level deconvolution led to multiple cell types, with significantly different TOO proportions between the two methods. This study thus outlines potential limitations of double-stranded library preparation for methylation analysis of cfDNA especially for urinary cfDNA. While the double-stranded method allows jagged end analysis in addition to TOO analysis, it leads to significant methylation bias in urinary cfDNA, which single-stranded methods can overcome.
ABSTRACT
In allograft monitoring of solid organ transplant recipients, liquid biopsy has emerged as a novel approach using quantification of donor-derived cell-free DNA (dd-cfDNA) in plasma. Despite early clinical implementation and analytical validation of techniques, direct comparisons of dd-cfDNA quantification methods are lacking. Furthermore, data on dd-cfDNA in urine is scarce and high-throughput sequencing-based methods so far have not leveraged unique molecular identifiers (UMIs) for absolute dd-cfDNA quantification. Different dd-cfDNA quantification approaches were compared in urine and plasma of kidney and liver recipients: A) Droplet digital PCR (ddPCR) using allele-specific detection of seven common HLA-DRB1 alleles and the Y chromosome; B) high-throughput sequencing (HTS) using a custom QIAseq DNA panel targeting 121 common polymorphisms; and C) a commercial dd-cfDNA quantification method (AlloSeq® cfDNA, CareDx). Dd-cfDNA was quantified as %dd-cfDNA, and for ddPCR and HTS using UMIs additionally as donor copies. In addition, relative and absolute dd-cfDNA levels in urine and plasma were compared in clinically stable recipients. The HTS method presented here showed a strong correlation of the %dd-cfDNA with ddPCR (R 2 = 0.98) and AlloSeq® cfDNA (R 2 = 0.99) displaying only minimal to no proportional bias. Absolute dd-cfDNA copies also correlated strongly (τ = 0.78) between HTS with UMI and ddPCR albeit with substantial proportional bias (slope: 0.25; 95%-CI: 0.19-0.26). Among 30 stable kidney transplant recipients, the median %dd-cfDNA in urine was 39.5% (interquartile range, IQR: 21.8-58.5%) with 36.6 copies/µmol urinary creatinine (IQR: 18.4-109) and 0.19% (IQR: 0.01-0.43%) with 5.0 copies/ml (IQR: 1.8-12.9) in plasma without any correlation between body fluids. The median %dd-cfDNA in plasma from eight stable liver recipients was 2.2% (IQR: 0.72-4.1%) with 120 copies/ml (IQR: 85.0-138) while the median dd-cfDNA copies/ml was below 0.1 in urine. This first head-to-head comparison of methods for absolute and relative quantification of dd-cfDNA in urine and plasma supports a method-independent %dd-cfDNA cutoff and indicates the suitability of the presented HTS method for absolute dd-cfDNA quantification using UMIs. To evaluate the utility of dd-cfDNA in urine for allograft surveillance, absolute levels instead of relative amounts will most likely be required given the extensive variability of %dd-cfDNA in stable kidney recipients.
